Glioblastoma is one of the most challenging forms of cancer to treat. Here we describe a computational platform that integrates the analysis of copy number variations and somatic mutations and unravels the landscape of in-frame gene fusions in glioblastoma. We found mutations with loss of heterozygosity in LZTR1, encoding an adaptor of CUL3-containing E3 ligase complexes. Mutations and deletions disrupt LZTR1 function, which restrains the self renewal and growth of glioma spheres that retain stem cell features. Loss-of-function mutations in CTNND2 target a neural-specific gene and are associated with the transformation of glioma cells along the very aggressive mesenchymal phenotype. We also report recurrent translocations that fuse the coding sequence of EGFR to several partners, with EGFR-SEPT14 being the most frequent functional gene fusion in human glioblastoma. EGFR-SEPT14 fusions activate STAT3 signaling and confer mitogen independence and sensitivity to EGFR inhibition. These results provide insights into the pathogenesis of glioblastoma and highlight new targets for therapeutic intervention.
Description
The integrated landscape of driver genomic alterations in glioblastoma. - PubMed - NCBI
%0 Journal Article
%1 Frattini:2013:Nat-Genet:23917401
%A Frattini, V
%A Trifonov, V
%A Chan, J M
%A Castano, A
%A Lia, M
%A Abate, F
%A Keir, S T
%A Ji, A X
%A Zoppoli, P
%A Niola, F
%A Danussi, C
%A Dolgalev, I
%A Porrati, P
%A Pellegatta, S
%A Heguy, A
%A Gupta, G
%A Pisapia, D J
%A Canoll, P
%A Bruce, J N
%A McLendon, R E
%A Yan, H
%A Aldape, K
%A Finocchiaro, G
%A Mikkelsen, T
%A Privé, G G
%A Bigner, D D
%A Lasorella, A
%A Rabadan, R
%A Iavarone, A
%D 2013
%J Nat Genet
%K glioblastoma untreated
%N 10
%P 1141-1149
%R 10.1038/ng.2734
%T The integrated landscape of driver genomic alterations in glioblastoma
%U https://www.ncbi.nlm.nih.gov/pubmed/23917401?dopt=Abstract&holding=npg
%V 45
%X Glioblastoma is one of the most challenging forms of cancer to treat. Here we describe a computational platform that integrates the analysis of copy number variations and somatic mutations and unravels the landscape of in-frame gene fusions in glioblastoma. We found mutations with loss of heterozygosity in LZTR1, encoding an adaptor of CUL3-containing E3 ligase complexes. Mutations and deletions disrupt LZTR1 function, which restrains the self renewal and growth of glioma spheres that retain stem cell features. Loss-of-function mutations in CTNND2 target a neural-specific gene and are associated with the transformation of glioma cells along the very aggressive mesenchymal phenotype. We also report recurrent translocations that fuse the coding sequence of EGFR to several partners, with EGFR-SEPT14 being the most frequent functional gene fusion in human glioblastoma. EGFR-SEPT14 fusions activate STAT3 signaling and confer mitogen independence and sensitivity to EGFR inhibition. These results provide insights into the pathogenesis of glioblastoma and highlight new targets for therapeutic intervention.
@article{Frattini:2013:Nat-Genet:23917401,
abstract = {Glioblastoma is one of the most challenging forms of cancer to treat. Here we describe a computational platform that integrates the analysis of copy number variations and somatic mutations and unravels the landscape of in-frame gene fusions in glioblastoma. We found mutations with loss of heterozygosity in LZTR1, encoding an adaptor of CUL3-containing E3 ligase complexes. Mutations and deletions disrupt LZTR1 function, which restrains the self renewal and growth of glioma spheres that retain stem cell features. Loss-of-function mutations in CTNND2 target a neural-specific gene and are associated with the transformation of glioma cells along the very aggressive mesenchymal phenotype. We also report recurrent translocations that fuse the coding sequence of EGFR to several partners, with EGFR-SEPT14 being the most frequent functional gene fusion in human glioblastoma. EGFR-SEPT14 fusions activate STAT3 signaling and confer mitogen independence and sensitivity to EGFR inhibition. These results provide insights into the pathogenesis of glioblastoma and highlight new targets for therapeutic intervention.},
added-at = {2017-05-17T18:56:55.000+0200},
author = {Frattini, V and Trifonov, V and Chan, J M and Castano, A and Lia, M and Abate, F and Keir, S T and Ji, A X and Zoppoli, P and Niola, F and Danussi, C and Dolgalev, I and Porrati, P and Pellegatta, S and Heguy, A and Gupta, G and Pisapia, D J and Canoll, P and Bruce, J N and McLendon, R E and Yan, H and Aldape, K and Finocchiaro, G and Mikkelsen, T and Priv{\'e}, G G and Bigner, D D and Lasorella, A and Rabadan, R and Iavarone, A},
biburl = {https://www.bibsonomy.org/bibtex/29a0660c107e1f97770d1a25777d8930b/marcsaric},
description = {The integrated landscape of driver genomic alterations in glioblastoma. - PubMed - NCBI},
doi = {10.1038/ng.2734},
interhash = {e7d8ebd7abdfdceb4c23f7341e372b7a},
intrahash = {9a0660c107e1f97770d1a25777d8930b},
journal = {Nat Genet},
keywords = {glioblastoma untreated},
month = oct,
number = 10,
pages = {1141-1149},
pmid = {23917401},
timestamp = {2017-05-17T18:56:55.000+0200},
title = {The integrated landscape of driver genomic alterations in glioblastoma},
url = {https://www.ncbi.nlm.nih.gov/pubmed/23917401?dopt=Abstract&holding=npg},
volume = 45,
year = 2013
}